Introducing ludwig - A Package for the Statistical Examination of Undirected Binary Networks
Undirected binary networks are interesting models for examining the stochastic associations between a set of objects that can take on two states. In psychology, these objects may be symptoms, items or the joint occurrence of words in data created by the pile-sort task. The package ludwig is similar in scope to the package IsingFit by van Borkulo, Epskamp and Robitzsch. However, the estimation method is inspired by an article by Strauss (1992), in which is described, how binary network models could be fit using the pseudolikelihood method, which reduces to a special form of multivariate logistic regression. In this talk, the basic functionality of ludwig (simulating data from networks and estimating parameters from data) and the respective algorithms will be explained. ludwig makes heavy use of glm(), glmnet() and qgraph(). The motivation of writing this package was to provide an experimental platform for researchers interested in network models and to implement a platform for further developments that would be interesting to discuss with the colleagues.